Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Heonkook Kim"'
Publikováno v:
Sensors, Vol 23, Iss 11, p 5299 (2023)
Cable is crucial to the control and instrumentation of machines and facilities. Therefore, early diagnosis of cable faults is the most effective approach to prevent system downtime and maximize productivity. We focused on a “soft fault state”, wh
Externí odkaz:
https://doaj.org/article/d238e2c4dc7444ed8a5a9c4d9f567def
Publikováno v:
Sensors, Vol 22, Iss 5, p 1917 (2022)
With the growth of factory automation, deep learning-based methods have become popular diagnostic tools because they can extract features automatically and diagnose faults under various fault conditions. Among these methods, a novelty detection appro
Externí odkaz:
https://doaj.org/article/c15cf61ec8fb4324aaa8aff9e7998a82
Publikováno v:
Sensors, Vol 21, Iss 17, p 5936 (2021)
We introduce a new approach for online and offline soft fault diagnosis in motor power cables, utilizing periodic burst injection and nonintrusive capacitive coupling. We focus on diagnosing soft faults because local cable modifications or soft fault
Externí odkaz:
https://doaj.org/article/d431f77bd389450094be4897ac2c583c
Publikováno v:
Sensors; Volume 23; Issue 11; Pages: 5299
Cable is crucial to the control and instrumentation of machines and facilities. Therefore, early diagnosis of cable faults is the most effective approach to prevent system downtime and maximize productivity. We focused on a “soft fault state”, wh
Publikováno v:
Sensors
Volume 21
Issue 17
Sensors (Basel, Switzerland)
Sensors, Vol 21, Iss 5936, p 5936 (2021)
Volume 21
Issue 17
Sensors (Basel, Switzerland)
Sensors, Vol 21, Iss 5936, p 5936 (2021)
We introduce a new approach for online and offline soft fault diagnosis in motor power cables, utilizing periodic burst injection and nonintrusive capacitive coupling. We focus on diagnosing soft faults because local cable modifications or soft fault